The analysis of trace gases in ambient air requires a preconcentration technique, in many cases to make the species of interest detectable and quantifiable. In this paper, such a preconcentration set-up is presented. Target species are trapped on adsorptive material cooled by a Stirling cooler which allows for a very low adsorption temperature but only requires electrical power. A simple and lightweight mechanical design guarantees very good suitability for remote-site field operation.

Emerging lower cost and miniaturized sensors have potential to increase spatial and temporal information on air pollution. To evaluate these technologies, air quality sensor devices were collocated with regulatory-grade instruments in a suburban outdoor setting in the southeastern United States. Additionally, a multi-node sensor network, with several nodes solar-powered and wirelessly transmitting data, was established to test the feasibility of high density, continuous air monitoring.

The accuracy of carbon models, used for the prediction of global climate change, is limited by the knowledge of the uptake of carbon by plants through photosynthesis. Carbonyl sulfide (COS) has been suggested as a tracer for this process. To be able to further explore and verify the application of this novel tracer we have tested a laser spectrometer for its suitability to obtain accurate and high precision measurements of COS and CO₂ with both laboratory experiments and field measurements.

Proton transfer reaction mass spectrometry (PTR-MS) was used to detect n-alkanes that generally have a lower proton affinity than water and therefore proton transfer (PT) by reaction with H₃O⁺ is not an effective mechanism for their detection. In this study, we developed a method using a conventional PTR-MS to detect n-alkanes by optimizing ion source and drift tube conditions to vary the relative amounts of different primary ions (H₃O⁺, O₂⁺, NO⁺) in the reaction chamber (drift tube).

Various carbonaceous materials are present in the atmosphere. Besides gaseous organic compounds, carbonaceous particles like soot are emitted into the air from traffic sources, residential wood combustion, or wildfires. Variable chemical compositions of such materials, which often result from incomplete combustion processes, show differences in the absorption behavior at visible wavelengths. Our instrument is able to measure the absorption at three visible wavelengths.

Air traffic at busy airports can be significantly disrupted because low visibility due to fog makes it unsafe to take off, land and taxi on the ground. In this paper we show how automatic profiling lidar ceilometer measurements, available at most airports, can be used to provide pre-fog alert information, and hence help airport weather forecasters to better predict these low visibility conditions. This research was carried out in the context of a field campaign at Paris CDG airport (France).

The data quality of radars must be ensured and continuously monitored. The aim of this paper is to provide an integrated approach able to monitor the calibration of operational dual-polarization radars. The set of methods considered appears suitable to establish an online tool to monitor the stability of the radar calibration with an accuracy of about 2 dB. This is considered adequate to automatically detect any unexpected change in the radar system requiring further investigations.

Application of global navigation satellite systems (GNSSs) for atmospheric remote sensing (GNSS meteorology) is a well-established field in both research and operation in Europe. This review covers the state of the art in GNSS meteorology in Europe. It discusses 1) advances in GNSS processing techniques and tropospheric products, 2) use in numerical weather prediction and nowcasting, and 3) climate research.

The detection of volcanic ash plumes and knowledge of their properties have been of increasing interest due to the effect ash particles can have on the aviation industry. A new method is shown for use with hyperspectral satellite instruments, such as the Infrared Atmospheric Sounding Interferometer, to derive optical and physical properties of volcanic ash. The results are compared to ancillary data sources, showing good agreement, which indicates better characterisation of volcanic plumes.

In 2017, the TROPOMI spectrometer will be launched on board the Sentinel 5 Precursor satellite. It will deliver, among other things, daily global measurements of methane as part of the Copernicus atmospheric services. In this paper, we present the algorithm that is used for operational data processing of the methane product from TROPOMI measurements of the shortwave and near-infrared spectral range, and we discuss its performance using realistic simulated measurements.

The objective of this paper is to describe the development and evaluate the performance of a totally new version of the Passive microwave Neural network Precipitation Retrieval (PNPR v2), an algorithm based on a neural network approach, designed to retrieve the instantaneous surface precipitation rate using the cross-track ATMS radiometer measurements.

Observations of the submillimetre part of the electromagnetic spectrum have previously been the domain of the astronomical community. However, new technological advances in the superconducting detectors field are offering the atmospheric sciences unexplored opportunities to perform useful spectroscopy in this region, exploiting existing radio telescope sites. Example simulations at six sites are presented for HBr, HOBr, HO₂ and N₂O showing the need for broad high-resolution measurements.

Volcanic eruptions pose a threat to human populations around the globe, but many active volcanoes are poorly monitored. This paper details the development of an automated volcanic plume detection method with focus on diffuse plumes, utilising daily, global observations of volcanic gases measured by satellites. The developed technique consistently distinguished volcanic plumes over 400 t, from control samples, indicating the potential for implementation within a volcanic alert system.

MIPAS is a satellite-borne limb emission sounder. The algorithm used to infer atmospheric composition from its measurements exploits the assumption that the atmosphere is horizontally homogeneous. This assumption can cause significant errors. We use synthetic observations to quantify these errors. Furthermore we show that the inclusion of any kind of horizontal variability model improves all the retrieval targets and that the two-dimensional approach implies the smallest errors.

The exchange of the greenhouse gases carbon dioxide and methane between the ocean and the atmosphere is of critical importance for the earth's climate. Despite this, direct measurements of these fluxes are relatively scarce, especially for methane, in large part due to instrumental challenges. In this paper, we evaluate the performance of two of the latest carbon dioxide and methane flux analysers. We also compare their detection limits to predicted air–sea fluxes of these gases.

A new methodology is presented to estimate regional-scale surface fluxes of ²²²Rn. ²²²Rn is an increasingly important trace gas which is used to calculate regional-scale greenhouse gas emissions and to validate atmospheric transport models. We tested our method at two atmospheric research stations in the Netherlands and compared our results with measurements from accumulation chambers and two recently published ²²²Rn soil flux maps for Europe.

Retrievals of aerosol microphysics exist for ground-based, airborne, and future space-borne lidar measurements. We investigate the information content of a lidar measurement system, using only a forward model but no explicit inversion. The simplified aerosol used here is applicable as a best case for all retrievals in the absence of additional constraints. We report (1) information content of the measurements; (2) uncertainties on the retrieved parameters; and (3) sources of compensating errors.

In this paper, we developed a new algorithm to improve the retrieval of aerosol optical depth (AOD) over land with satellite measurement by refining the shape of the spectral surface reflectance to improve the estimated background reflectance in the channel used for AOD retrieval. The results show that the angular effects of the retrievals are largely reduced, including fewer occurrences of negative retrievals. This implies that the users can get more accurate data without angular bias.

During the BORTAS aircraft campaign, we measured NO₂ and their oxidtation products (as peroxy nitrates) with a custom laser-induced fluorescence instrument. Because of the high correlation between known pyrogenic tracers (i.e., carbon monoxide) and peroxy nitrates, we provide two methods to use these species for the identification of biomass burning (BB) plumes. Using an artifical neural network, we improved the BB identification taking into account of a meteorological parameter (pressure).

Stratospheric Air Sub-sampler (SAS) is a device to collect and to store the stratospheric profile of air collected with an AirCore (Karion et al., 2010) in numerous sub-samples. The sub-samples (each of 25 mL at ambient temperature and pressure) can be later introduced to the continuous flow systems to measure for example the isotopic composition of CO₂. The performance of the coupled system is demonstrated for a set of air samples from an AirCore flight in November 2014 near Sodankylä, Finland.

Profiles of CFC-11, CFC-12 and HCFC-22 have been obtained from FTIR measurements above the Saint-Denis and Maïdo sites at Reunion Island (21° S, 55° E) with low vertical resolution. The trends derived from the FTIR measurements are −0.86 ± 0.12 % and 2.84 ± 0.06 % for CFC-11 and HCFC-22, respectively, for the period 2004 to 2016, and −0.76 ± 0.05 % for CFC-12 for 2009 to 2016, which are consistent with ground-based in situ observations. Our FTIR data and the collocated MIPAS data are in good agreement.

The binning method provides an alternate way to process GC–MS data in a very fast manner. It only takes a very small portion of time (days versus years) compared to the traditional GC–MS data analysis method (peak identification and integration). Furthermore, the binning method can also be applied to any data set from a measurement (mass spectrometry, spectroscopy, etc.) with additional separations (volatility, polarity, size, etc.).

We present a parameterization method for the conversion of measured trace gas slant column densities into volume mixing ratios along a flight track. Benefits of this method are that it is computationally fast and almost no information on local atmospheric conditions is needed. Application to simulated data and field data show that the method is accurate within 10–15 % and valid for a wide range of atmospheric conditions. Our method can easily be transferred to other trace gases.